摘要
针对室外视频包含噪声、复杂气象条件等引起的视频退化问题,对噪声特点及前景目标运动性质的差异进行分析,提出一种二次前景分割方法.使用窗口序列PCA并结合高斯混合模型对室外视频降噪后进行背景建模,初次分割前景目标;通过分析目标重叠区域概率描述不同前景目标的运动性质,并结合初次分割结果对视频进行二次分割,提取感兴趣目标;对雨、雪等非感兴趣目标进行背景修饰,提高视频数据质量.实验结果表明,该方法能够有效地抑制室外视频噪声,去除雨、雪影响,改善视觉效果.
Noise characteristic and motion properties of different foreground objects under various weather conditions are analyzed for outdoor videos,and a primary-secondary foreground segmentation method is proposed.A window series PCA algorithm,combined with the Gaussian mixture model,is used to model the videos after de-nosing and segmenting all foreground objects primarily.After that,the probabilities of the overlapped regions are calculated to describe the motion properties of different objects,and a second segmentation step is carried out to extract the interesting objects.Finally,the uninteresting objects,such as raindrops and snowflakes,are treated via a background-inpainting step to improve the video quality.Experimental results show that our proposed method can effectively reduce noise,diminish the interference of rain or snow,and enhance video effects.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2010年第9期1545-1553,共9页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60706032)
中国空间技术研究院创新基金(CAST200814)
哈尔滨工业大学科研创新基金(HIT.NSRIF.2008.63)
关键词
窗口序列PCA
二次前景分割
去雨雪
高斯混合模型
视频处理
window series PCA
primary-secondary foreground segmentation
rain and snow removal
Gaussian mixture model
video processing
